IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/62047.html
   My bibliography  Save this paper

Stock-Flow Dynamic Projection

Author

Listed:
  • LI, XI HAO
  • Gallegati, Mauro

Abstract

Borrowing from our experience in agent-based computational economic research from `bottom-up', this paper considers economic system as multi-level dynamical system that micro-level agents' interaction leads to structural transition in meso-level, which results in macro-level market dynamics with endogenous fluctuation or even market crashes. By the concept of transition matrix, we develop technique to quantify meso-level structural change induced by micro-level interaction. Then we apply this quantification to propose the method of dynamic projection that delivers out-of-sample forecast of macro-level economic variable from micro-level big data. We testify this method with a data set of financial statements for 4599 firms listed in Tokyo Stock Exchange for the year of 1980 to 2012. The Diebold-Mariano test indicates that the dynamic projection has significantly higher accuracy for one-period-ahead out-of-sample forecast than the benchmark of ARIMA models.

Suggested Citation

  • LI, XI HAO & Gallegati, Mauro, 2015. "Stock-Flow Dynamic Projection," MPRA Paper 62047, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:62047
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/62047/1/MPRA_paper_62047.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Foley Duncan K., 1994. "A Statistical Equilibrium Theory of Markets," Journal of Economic Theory, Elsevier, vol. 62(2), pages 321-345, April.
    2. Engel, Charles & Hamilton, James D, 1990. "Long Swings in the Dollar: Are They in the Data and Do Markets Know It?," American Economic Review, American Economic Association, vol. 80(4), pages 689-713, September.
    3. Troy Davig & Eric M. Leeper, 2008. "Endogenous Monetary Policy Regime Change," NBER Chapters, in: NBER International Seminar on Macroeconomics 2006, pages 345-391, National Bureau of Economic Research, Inc.
    4. Luca Riccetti & Alberto Russo & Mauro Gallegati, 2015. "An agent based decentralized matching macroeconomic model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(2), pages 305-332, October.
    5. Troy Davig & Eric M. Leeper, 2007. "Generalizing the Taylor Principle," American Economic Review, American Economic Association, vol. 97(3), pages 607-635, June.
    6. Chang-Jin Kim & Charles R. Nelson, 1998. "Business Cycle Turning Points, A New Coincident Index, And Tests Of Duration Dependence Based On A Dynamic Factor Model With Regime Switching," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 188-201, May.
    7. Xiaoshan Chen & Ronald Macdonald, 2012. "Realized and Optimal Monetary Policy Rules in an Estimated Markov‐Switching DSGE Model of the United Kingdom," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(6), pages 1091-1116, September.
    8. Gatti, Domenico Delli & Gallegati, Mauro & Greenwald, Bruce C. & Russo, Alberto & Stiglitz, Joseph E., 2012. "Mobility constraints, productivity trends, and extended crises," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 375-393.
    9. Sims, Christopher A. & Waggoner, Daniel F. & Zha, Tao, 2008. "Methods for inference in large multiple-equation Markov-switching models," Journal of Econometrics, Elsevier, vol. 146(2), pages 255-274, October.
    10. Christopher A. Sims & Tao Zha, 2006. "Were There Regime Switches in U.S. Monetary Policy?," American Economic Review, American Economic Association, vol. 96(1), pages 54-81, March.
    11. Garcia, Rene & Perron, Pierre, 1996. "An Analysis of the Real Interest Rate under Regime Shifts," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 111-125, February.
    12. Lux, Thomas, 2008. "Applications of statistical physics in finance and economics," Kiel Working Papers 1425, Kiel Institute for the World Economy (IfW Kiel).
    13. Andrew T. Foerster, 2016. "Monetary Policy Regime Switches And Macroeconomic Dynamics," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57(1), pages 211-230, February.
    14. Aoki,Masanao, 1998. "New Approaches to Macroeconomic Modeling," Cambridge Books, Cambridge University Press, number 9780521637695, September.
    15. Goodwin, Thomas H, 1993. "Business-Cycle Analysis with a Markov-Switching Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(3), pages 331-339, July.
    16. Aoki,Masanao, 2004. "Modeling Aggregate Behavior and Fluctuations in Economics," Cambridge Books, Cambridge University Press, number 9780521606196, September.
    17. Battiston, Stefano & Delli Gatti, Domenico & Gallegati, Mauro & Greenwald, Bruce & Stiglitz, Joseph E., 2012. "Liaisons dangereuses: Increasing connectivity, risk sharing, and systemic risk," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1121-1141.
    18. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    19. Zheng Liu & Daniel F. Waggoner & Tao Zha, 2011. "Sources of macroeconomic fluctuations: A regime‐switching DSGE approach," Quantitative Economics, Econometric Society, vol. 2(2), pages 251-301, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Venables, Anthony J., 2017. "Breaking into tradables: Urban form and urban function in a developing city," Journal of Urban Economics, Elsevier, vol. 98(C), pages 88-97.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shayan Zakipour-Saber, 2019. "Monetary policy regimes and inflation persistence in the United Kingdom," Working Papers 895, Queen Mary University of London, School of Economics and Finance.
    2. Reuben Ellul, "undated". "Timing the Maltese business cycle: A historical perspective," CBM Working Papers WP/01/2021, Central Bank of Malta.
    3. Choi, Jinho & Hur, Joonyoung, 2015. "An examination of macroeconomic fluctuations in Korea exploiting a Markov-switching DSGE approach," Economic Modelling, Elsevier, vol. 51(C), pages 183-199.
    4. Yoosoon Chang & Fei Tan & Xin Wei, 2018. "State Space Models with Endogenous Regime Switching," CAEPR Working Papers 2018-012, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    5. Stéphane Lhuissier & Fabien Tripier, 2021. "Regime‐dependent effects of uncertainty shocks: A structural interpretation," Quantitative Economics, Econometric Society, vol. 12(4), pages 1139-1170, November.
    6. Chung-Ming Kuan, 2013. "Markov switching model (in Russian)," Quantile, Quantile, issue 11, pages 13-40, December.
    7. Lhuissier, Stéphane & Zabelina, Margarita, 2015. "On the stability of Calvo-style price-setting behavior," Journal of Economic Dynamics and Control, Elsevier, vol. 57(C), pages 77-95.
    8. Nurgun Topalli & İbrahim Dogan, 2016. "The structure and sustainability of current account deficit: Turkish evidence from regime switching," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 25(4), pages 570-589, June.
    9. Andrew Foerster & Juan F. Rubio‐Ramírez & Daniel F. Waggoner & Tao Zha, 2016. "Perturbation methods for Markov‐switching dynamic stochastic general equilibrium models," Quantitative Economics, Econometric Society, vol. 7(2), pages 637-669, July.
    10. Baele, Lieven & Bekaert, Geert & Cho, Seonghoon & Inghelbrecht, Koen & Moreno, Antonio, 2015. "Macroeconomic regimes," Journal of Monetary Economics, Elsevier, vol. 70(C), pages 51-71.
    11. Fiorentini, Gabriele & Planas, Christophe & Rossi, Alessandro, 2016. "Skewness and kurtosis of multivariate Markov-switching processes," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 153-159.
    12. Dennis Wesselbaum, 2022. "Cheap Talk in a New Keynesian Model," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(3), pages 661-691, September.
    13. Andrew T. Foerster, 2016. "Monetary Policy Regime Switches And Macroeconomic Dynamics," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57(1), pages 211-230, February.
    14. Polbin, Andrey & Shumilov, Andrei & Bedin, Andrei & Kulikov, Alexander, 2019. "Modeling real exchange rate of the Russian ruble using Markov regime switching approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 55, pages 32-50.
    15. Carboni, Giacomo, 2014. "Term premia implications of macroeconomic regime changes," Working Paper Series 1694, European Central Bank.
    16. Xiaoshan Chen & Ronald Macdonald, 2012. "Realized and Optimal Monetary Policy Rules in an Estimated Markov‐Switching DSGE Model of the United Kingdom," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(6), pages 1091-1116, September.
    17. Robert Dixon & Zhichao Zhang & Yang Dai, 2016. "Exchange Rate Flexibility in China: Measurement, Regime Shifts and Driving Forces of Change," Review of International Economics, Wiley Blackwell, vol. 24(5), pages 875-892, November.
    18. James D. Hamilton & Tatsuyoshi Okimoto, 2011. "Sources of variation in holding returns for fed funds futures contracts," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(3), pages 205-229, March.
    19. Kasahara, Hiroyuki & Shimotsu, Katsumi, 2019. "Asymptotic properties of the maximum likelihood estimator in regime switching econometric models," Journal of Econometrics, Elsevier, vol. 208(2), pages 442-467.
    20. Polbin, Andrey & Shumilov, Andrei & Bedin, Andrey & Kulikov, Alexander, 2019. "Модель Реального Обменного Курса Рубля С Марковскими Переключениями Режимов [Modeling real exchange rate of the Russian ruble using Markov regime-switching approach]," MPRA Paper 93310, University Library of Munich, Germany.

    More about this item

    Keywords

    economic forecasting; dynamic projection; multi-level dynamical system; transition matrix;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:62047. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.